Genomic approaches to outcome prediction in prostate cancer

DNA alterations in the tumor genome and their associations with clinical outcome in prostate cancer

Although most prostate cancer (PCa) cases are not life-threatening, approximately 293 000 men worldwide die annually due to PCa. These lethal cases are thought to be caused by coordinated genomic alterations that accumulate over time. Recent genome-wide analyses of DNA from subjects with PCa have revealed most, if not all, genetic changes in both germline and PCa tumor genomes. In this article, I first review the major, somatically acquired genomic characteristics of various subtypes of PCa. I then recap key findings on the relationships between genomic alterations and clinical parameters, such as biochemical recurrence or clinical relapse, metastasis and cancer-specific mortality. Finally, I outline the need for, and challenges with, validation of recent findings in prospective studies for clinical utility. It is clearer now than ever before that the landscape of somatically acquired aberrations in PCa is highlighted by DNA copy number alterations (CNAs) and TMPRSS2-ERG fusion derived from complex rearrangements, numerous single nucleotide variations or mutations, tremendous heterogeneity, and continuously punctuated evolution. Genome-wide CNAs, PTEN loss, MYC gain in primary tumors, and TP53 loss/mutation and AR amplification/mutation in advanced metastatic PCa have consistently been associated with worse cancer prognosis. With this recently gained knowledge, it is now an opportune time to develop DNA-based tests that provide more accurate patient stratification for prediction of clinical outcome, which will ultimately lead to more personalized cancer care than is possible at present.

Clinically relevant genetic characterization of prostate tumors: how close are we to the goal?

Substantial efforts are being made in research on the molecular genetic characterization of prostate cancer. The number of fundamental research programs in prostate cancer molecular biology and genetics is overwhelming. However, a significant gap appears to exist between the huge number of studies on the genetic characterization of prostate cancer, which often have limited translation into clinical practice or simply were not conceived to be so translated, and clinical practice. From a clinical point of view, this balance should be urgently shifted towards rapid translation into urological practice. However, prostate cancer is characterized by prominent genetic heterogeneity, which could be a very difficult barrier to overcome. In this review, we discuss the possible clinical applications of scientific data from fundamental studies of prostate cancer genetics, the main problems with the translation of these data to clinics, and future perspectives.

Genomic analysis in active surveillance: predicting high-risk disease using tissue biomarkers

PURPOSE OF REVIEW

For patients newly diagnosed with prostate cancer, the most significant question is whether the 'truly malignant' disease has been identified. This review will provide an overview of current prostate cancer genomic and biomarker discovery - validation strategies geared towards identifying aggressive, clinically significant disease at the time of diagnosis.

RECENT FINDINGS

Based on recent findings the prostate cancer aggressive disease phenotype develops as a result of mutations (TP53, PTEN), structural events (TMPRSS2-ETS), epigenetic changes (EZH2, DAB2IP, histone alteration), and transcriptional modifications (SChLAP, PCAT-1). Copy number variability and dysregulation of specific pathways including androgen receptor signaling, PTEN/PAKT and TGF-β continue to play an important role in invasion and metastasis.

SUMMARY

Given the current challenges for applying prostate cancer genomics to clinical management, this review will incorporate some of the current novel genomic approaches and techniques including systems-based precise pathology platforms, and the role of fluid-based assays, notably, exosomes and circulating tumor cells (liquid biopsy), as tools for future diagnostic-treatment algorithms.

Performance of an adipokine pathway-based multilocus genetic risk score for prostate cancer risk prediction

Few biomarkers are available to predict prostate cancer risk. Single nucleotide polymorphisms (SNPs) tend to have weak individual effects but, in combination, they have stronger predictive value. Adipokine pathways have been implicated in the pathogenesis. We used a candidate pathway approach to investigate 29 functional SNPs in key genes from relevant adipokine pathways in a sample of 1006 men eligible for prostate biopsy. We used stepwise multivariate logistic regression and bootstrapping to develop a multilocus genetic risk score by weighting each risk SNP empirically based on its association with disease. Seven common functional polymorphisms were associated with overall and high-grade prostate cancer (Gleason≥7), whereas three variants were associated with high metastatic-risk prostate cancer (PSA≥20 ng/mL and/or Gleason≥8). The addition of genetic variants to age and PSA improved the predictive accuracy for overall and high-grade prostate cancer, using either the area under the receiver-operating characteristics curves (P<0.02), the net reclassification improvement (P<0.001) and integrated discrimination improvement (P<0.001) measures. These results suggest that functional polymorphisms in adipokine pathways may act individually and cumulatively to affect risk and severity of prostate cancer, supporting the influence of adipokine pathways in the pathogenesis of prostate cancer. Use of such adipokine multilocus genetic risk score can enhance the predictive value of PSA and age in estimating absolute risk, which supports further evaluation of its clinical significance.

The genomic landscape of prostate cancer

Prostate cancer is a common malignancy in men, with a markedly variable clinical course. Somatic alterations in DNA drive the growth of prostate cancers and may underlie the behavior of aggressive versus indolent tumors. The accelerating application of genomic technologies over the last two decades has identified mutations that drive prostate cancer formation, progression, and therapeutic resistance. Here, we discuss exemplary somatic mutations in prostate cancer, and highlight mutated cellular pathways with biological and possible therapeutic importance. Examples include mutated genes involved in androgen signaling, cell cycle regulation, signal transduction, and development. Some genetic alterations may also predict the clinical course of disease or response to therapy, although the molecular heterogeneity of prostate tumors poses challenges to genomic biomarker identification. The widespread application of massively parallel sequencing technology to the analysis of prostate cancer genomes should continue to advance both discovery-oriented and diagnostic avenues.

Derivation of cancer diagnostic and prognostic signatures from gene expression data

The ability to compare genome-wide expression profiles in human tissue samples has the potential to add an invaluable molecular pathology aspect to the detection and evaluation of multiple diseases. Applications include initial diagnosis, evaluation of disease subtype, monitoring of response to therapy and the prediction of disease recurrence. The derivation of molecular signatures that can predict tumor recurrence in breast cancer has been a particularly intense area of investigation and a number of studies have shown that molecular signatures can outperform currently used clinicopathologic factors in predicting relapse in this disease. However, many of these predictive models have been derived using relatively simple computational algorithms and whether these models are at a stage of development worthy of large-cohort clinical trial validation is currently a subject of debate. In this review, we focus on the derivation of optimal molecular signatures from high-dimensional data and discuss some of the expected future developments in the field.

Axillary lymph node metastasis and survival in breast cancer patients with concurrent cardio-cerebral-vascular disease

Objectives

Dissemination of tumour cells occurring both spontaneously or caused by diagnostic biopsy procedures is the most serious complication of solid malignancies. In the present work we focus on local tumour spread and how this complication of cancer disease can be counteracted.

Design

From a cohort of 864 breast cancer patients we selected those who died of their primary cancer and those who died because of a simultaneously existing cardio-cerebral-vascular disease (CCVD) and were exposed to anticoagulants.

Setting

The study was based on breast cancer patients diagnosed at Karolinska University Hospital during 1991 (n = 519) and 1997–1998 (n = 345).

Main outcome measures

Axillary lymph node metastasis (ALNM) and survival of breast cancer patients with concurrent CCVD.

Results

Breast cancer patients belonging to the group that died of CCVD showed ALNM at the time of tumour diagnosis in 27% of the cases compared with 68% diagnosed in the group that died of their breast cancer (p < 0.0001). Likewise we observed a highly significant (p < 0.0001) difference in mean survival time with an average of 102 months in the group of breast cancer patients who died of CCVD and an average of 61 months in the group who died of breast cancer.

Conclusion

The data presented herein indicate that breast cancer patients regularly involved in treatment with anticoagulants because of simultaneously existing CCVD develop ALNM significantly less frequently and have an increased average survival time compared with breast cancer patients not suffering from CCVD.

Invasive prostate carcinoma driven by c-Src and androgen receptor synergy

Cellular Src (c-Src) integrates a large number of signal transduction pathways regulating cell division, migration, and other aspects of cell physiology. Mutations of Src kinase have not been described in human prostate cancer, but evidence for increased levels of expression accompanying cancer progression has been reported. We analyzed overexpression of c-Src in naïve mouse prostate epithelium and observed no change in tubule formation frequency or histologic structure. However, when enhanced c-Src expression is coupled with enhanced expression of androgen receptor (AR), it results in a strong activation of Src kinase activity accompanied by activation of the MAPK pathway, and enhanced AR activity. Similar to the pathology induced by constitutively active c-Src(Y529F), the tubules progress to frank carcinoma with invasion and display markers of epithelial-to-mesenchymal transition. These combined results suggest that nonmutated Src kinase may play a more important role in the genesis and progression of prostate cancer than previously appreciated and that epigenetic changes that enhance the level of AR may select for enhanced expression of c-Src with accompanying activation and a strong drive to malignant progression.

The use of COLD-PCR and high-resolution melting analysis improves the limit of detection of KRAS and BRAF mutations in colorectal cancer

Fast and reliable tests to detect mutations in human cancers are required to better define clinical samples and orient targeted therapies. KRAS mutations occur in 30-50% of colorectal cancers (CRCs) and represent a marker of clinical resistance to cetuximab therapy. In addition, the BRAF V600E is mutated in about 10% of CRCs, and the development of a specific inhibitor of mutant BRAF kinase has prompted a growing interest in BRAF (V600E) detection. Traditional methods, such as PCR and direct sequencing, do not detect low-level mutations in cancer, resulting in false negative diagnoses. In this study, we designed a protocol to detect mutations of KRAS and BRAF(V600E) in 117 sporadic CRCs based on coamplification at lower denaturation temperature PCR (COLD-PCR) and high-resolution melting (HRM). Using traditional PCR and direct sequencing, we found KRAS mutations in 47 (40%) patients and BRAF(V600E) in 10 (8.5%). The use of COLD-PCR in apparently wild-type samples allowed us to identify 15 newly mutated CRCs (10 for KRAS and 5 for BRAF (V600E)), raising the percentage of mutated CRCs to 48.7% for KRAS and to 12.8% for BRAF (V600E). Therefore, COLD-PCR combined with HRM permits the correct identification of less represented mutations in CRC and better selection of patients eligible for targeted therapies, without requiring expensive and time-consuming procedures.

Src kinase inhibitors: an emerging therapeutic treatment option for prostate cancer

IMPORTANCE OF THE FIELD

Once prostate cancer becomes castration-resistant, bone metastases are a significant problem and treatment options are limited. As a result, there is a need for more effective therapies that have antitumor and anti-bone metastatic effects. Because Src and Src-family kinases (SFKs) are involved in multiple signaling pathways central to prostate cancer development, progression, and metastasis, in addition to normal and pathologic osteoclast activities, Src inhibition represents a valid therapeutic strategy for investigation.

AREAS COVERED IN THIS REVIEW

Here, current treatment options for advanced prostate cancer, the preclinical rationale behind using Src inhibitors, emerging data from clinical trials of Src inhibitors in prostate cancer, and future therapeutic directions are described. Data published in peer-reviewed journals within the last 20 years or presented at recent European or American Society of Clinical Oncology conferences have been reviewed.

WHAT THE READER WILL GAIN

Readers will gain an insight into the development of therapeutic Src inhibitors, including dasatinib and saracatinib; an understanding of their effects on prostate cancer cells and the bone microenvironment; and emerging clinical data.

TAKE HOME MESSAGE

Src is implicated in prostate cancer progression and metastasis, therefore treatment with Src inhibitors warrants further investigation.

Molecular circuits of solid tumors: prognostic and predictive tools for bedside use

The explosion of knowledge in cancer biology in the past two decades has led to the identification of specific molecular circuits in solid tumors. These pathways reflect specific abnormalities thought to drive malignant progression. This knowledge has also generated a vast panel of cancer biomarkers although many of these biomarkers lack sufficient research and validation to be used in the clinic. This Review discusses relevant molecular prognostic and/or predictive biomarkers in the six leading tumors with the highest contribution to cancer mortality: breast, lung, colorectal, prostate, pancreatic and ovarian cancer. Each biomarker is described according to its associated clinicopathological presentation and specific associated molecular interactions. Despite only few biomarkers being currently implemented in clinical practice, a new generation of predictors is emerging that could modify the classic organ-based cancer classification (for example, defects in DNA repair, aberrant MAPK signaling and aberrant PI3K/Akt/mTOR signaling). The advent of high-throughput strategies will also probably substitute monobiomarker strategies.

Molecular epidemiology and its current clinical use in cancer management

The revelation of the entire human DNA sequence in 2001, and the launching of the international haplotype map (HapMap) project, made the identification of common markers of disease possible, dramatically transforming molecular epidemiology. In recent years, the development of, and discoveries within, human genome research have been rapid, highlighted by the current explosion of genome-wide association studies (GWAS). GWAS aim at finding germline changes that increase cancer risk. An equally important and rapid development had been seen in cancer genomics, with great strides being made in our understanding of somatic mutations that allow and accompany cancer development. In this review we discuss whether it is currently possible to use these new discoveries to aid the reduction of cancer mortality by reducing risk of disease, improving prognosis, and keeping complications due to treatment to a minimum. Findings from GWAS have mostly been used to predict risk, but there is the potential to use them for prognostication and even treatment prediction. Expression arrays have identified prognostic patterns for breast cancer, but few reliable patterns are available for treatment prediction. More importantly, virtually no genetic signatures are available to predict morbidity from treatment. Thus, there is a need to bring different biological techniques together and integrate them with existing clinical oncological care for a simultaneous risk and outcome assessment.

Blood and tissue biomarkers in prostate cancer: state of the art

The prevalence of prostate cancer (PCa) is high and increases with age. PCa is the most common cutaneous cancer in American men. Prostate-specific antigen (PSA) screening has impacted the detection of PCa and is directly responsible for a dramatic decrease in stage at diagnosis. Gleason score and stage at the time of diagnosis remain the mainstay to predict prognosis, in the absence of more accurate and reliable tissue or blood biomarkers. Despite extensive research efforts, very few biomarkers of PCa have been introduced to date in clinical practice. Even screening with PSA has recently been questioned. A thorough analysis of all tissue and serum biomarkers in prostate cancer research cannot be easily synthesized, and goes beyond the scope of the present article. Therefore the authors focus here on the most recently reported tissue and circulating biomarkers for PCa whose application in clinical practice is either current or expected in the near future.